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  • Title: A Connectomic Atlas of the Human Cerebrum-Chapter 18: The Connectional Anatomy of Human Brain Networks.
    Author: Briggs RG, Conner AK, Baker CM, Burks JD, Glenn CA, Sali G, Battiste JD, O'Donoghue DL, Sughrue ME.
    Journal: Oper Neurosurg (Hagerstown); 2018 Dec 01; 15(suppl_1):S470-S480. PubMed ID: 30260432.
    Abstract:
    BACKGROUND: It is widely understood that cortical functions are mediated by complex, interdependent brain networks. These networks have been identified and studied using novel technologies such as functional magnetic resonance imaging under both resting-state and task-based conditions. However, no one has attempted to describe these networks in terms of their cortical parcellations. OBJECTIVE: To describe our approach to network modeling and discuss its significance for the future of neuronavigation in brain surgery using the cortical parcellation scheme detailed within this supplement. METHODS: Using network models previously elucidated by our group using coordinate-based meta-analytic techniques, we show the anatomic position and underlying white matter tracts of the cortical regions comprising 8 functional networks of the human cerebrum. These network models are displayed using Synaptive's clinically available BrightMatter tractography software (Synaptive Medical, Toronto, Canada). RESULTS: The relevant cortical parcellations of 8 different cerebral networks have been identified. The fiber tracts between these regions were used to construct anatomically precise models of the networks. Models are described for the dorsal attention, ventral attention, semantic, auditory, supplementary motor, ventral premotor, default mode, and salience networks. CONCLUSION: Our goal is to move towards more precise, anatomically specific models of brain networks that can be constructed for individual patients and utilized in navigational platforms during brain surgery. We believe network modeling and future advances in navigation technology can provide a foundation for improving neurosurgical outcomes by allowing us to preserve complex brain networks.
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